Is Your University Visible on ChatGPT? A 5-Step Diagnostic

Why this diagnostic is urgent

Your future students no longer start their research on Google. In 2026, 41% of 16-to-24-year-olds use an AI engine (ChatGPT, Perplexity, Gemini) as their first point of contact when researching post-secondary education (Source: UCAS/Savanta survey, Jan 2026, 4,200 UK sixth-formers and undergraduates). That figure was 12% in 2024. The shift is underway, and it is fast.

The question is no longer whether AI engines influence student recruitment. It is whether your institution appears in their answers — or whether only your competitors do.

This diagnostic takes 30 minutes, requires no paid tools and produces a prioritised correction plan.

Step 1: Test your branded queries

Branded queries are the most basic: the prospect types your institution's name directly into an AI engine. If the AI does not know you by name, the problem is serious.

The 3 prompts to test

Submit these three prompts to ChatGPT, Perplexity and Gemini (9 tests total):

1. "What do you know about [your university]?" — The engine should return: full name, location, degree types, accreditations, general positioning
2. "[Your university] student reviews" — The engine should cite student feedback, scores or testimonials
3. "[Your university] tuition fees and graduate outcomes" — The engine should provide concrete figures

Scoring grid

For each response, score on 4 points:

Score /12 per engine (3 prompts x 4 criteria). A score below 6 on any engine means your institution is poorly referenced in its corpus. A score of 0 means you are invisible.

Average score observed across 50 institutions tested: 4.2/12 on ChatGPT, 5.8/12 on Perplexity, 3.1/12 on Gemini (Source: Skolbot GEO diagnostic, panel of 50 European institutions, Feb 2026). Russell Group universities average 7.1/12. Post-92 universities average 2.8/12.

Step 2: Test your generic queries

Generic queries are the most strategic. The prospect is not searching for your institution specifically — they are searching for "the best business school in London" or "an MBA with placements." These are the queries where the visibility battle is fought.

The 5 prompts to test

Adapt these prompts to your context (city, discipline, level):

1. "What are the best [type of institution] in [city]?" — Example: "What are the best business schools in Manchester?"
2. "What course should I study to work in [field]?" — Example: "What course should I study to work in data science?"
3. "[Type of institution] with placements in [city/region]" — Example: "Engineering university with placements in the Midlands"
4. "Comparison [your university] vs [competitor]" — Example: "Warwick vs Bath"
5. "Reviews of [type of course] in the UK for international students" — Example: "Reviews of MBA programmes in the UK for international students"

Scoring grid

For each prompt, score:

Maximum score: 20 points (5 prompts x 4 points). A score below 5 means your institution is absent from AI recommendations for its strategic queries.

Across 50 institutions tested, 72% score 0 on ChatGPT's generic queries — they are simply never mentioned (Source: Skolbot GEO diagnostic, Feb 2026). On Perplexity, that figure drops to 54%, confirming that Perplexity is more permeable to recent content.

Step 3: Audit your structured data

Schema.org structured data is the most actionable technical lever. This step takes 5 minutes per page.

The 3-click test

1. Open the Google Rich Results Test
2. Enter your homepage URL, then a programme page URL
3. Check for the following schemas:

If none of these schemas are detected, your site is technically invisible to AI engines. This is the case for 82% of European institutions (Source: Skolbot technical audit, 120 institutions, Jan 2026).

To implement these schemas, our guide to structured data for universities details the process with JSON-LD code examples.

Step 4: Evaluate your verifiable data density

AI engines cite facts, not slogans. This step assesses the richness of verifiable data on your key pages.

The entity-counting method

Open your 5 most visited pages (homepage, main programme page, admissions page, fees page, student life page) and count for each:

• Sourced figures — Employment rate, salary, student numbers, ranking position, with a verifiable source
• Named entities — Accreditations (AACSB, TEF), organisations (OfS, UCAS), rankings (QS, THE), named partners
• Precise dates — 2026 intake, HESA Graduate Outcomes 2025, QS Ranking 2026

Scoring

The observed median is 2.3 verifiable data points per page across European university websites (Source: Skolbot semantic analysis, 800 pages from 120 institutions, Feb 2026). The top 10 GEO institutions show a median of 8.7 verifiable data points per page.

The gap is considerable. It alone explains why some institutions are systematically cited while others are systematically ignored.

Step 5: Map your external mentions

AI engines cross-reference sources. The more your institution is mentioned on trusted third-party sites, the more it is considered notable and reliable.

The 12-source checklist

Check whether your institution is listed (with current information) on each of these sites:

Scoring

Institutions present on 7+ third-party sources are 3.2x more likely to be cited by an AI engine than those on 3 or fewer (Source: Skolbot GEO correlation analysis, 120 institutions, Feb 2026).

Diagnostic summary: your overall score

Add your scores across the 5 steps to get your AI visibility profile:

Interpretation

• Profile A (high scores throughout) — Well positioned. Maintain freshness and monitor quarterly
• Profile B (strong on brand, weak on generic) — The AI knows you but does not recommend you. Work on structured content and verifiable data
• Profile C (low throughout except mentions) — Your reputation exists but your site does not reflect it. Priority: Schema.org
• Profile D (low throughout) — Full overhaul needed. The plan below is your roadmap

Prioritised correction plan

Priority 1 — Week 1: the technical foundation

Implement Schema.org (EducationalOrganization, Course, FAQPage) on your key pages. A developer can do this in 3 to 5 days.

Priority 2 — Week 2: content enrichment

Add verifiable data to your 5 most visited pages: sourced employment rate, median salary, named accreditations. Target: 8+ verifiable data points per page.

Priority 3 — Week 3: structured FAQs

Create marked-up FAQs on your admissions and programme pages. Answer the most common questions prospects ask.

Priority 4 — Weeks 4-8: external mentions

Update your listings on UCAS, OfS, HESA, QS, THE. Complete your Google Business Profile and encourage student reviews.

Priority 5 — Ongoing: freshness

Quarterly update of programme pages. Two blog posts per month minimum.

For a deep understanding of GEO strategy in higher education, our complete GEO guide for universities covers the 5 pillars of AI visibility. Once the diagnosis is done, structure your response with our 90-day action plan to get cited by ChatGPT and Perplexity.